Introduction
Diabetes mellitus represents one of the most pressing global health challenges of the 21st century. According to the International Diabetes Federation, the number of individuals living with diabetes is projected to reach 783 million by 2045(1). This rising prevalence highlights the substantial public health impact of diabetes, which leads to serious complications such as cardiovascular disease, nephropathy, and retinopathy, and in turn contributes to reduced quality of life and increased morbidity. These complications place a significant burden on healthcare systems and economies worldwide (2). Early diagnosis and regular monitoring are therefore essential to prevent long term complications, optimize glycemic control, and improve clinical outcomes (3).
Hemoglobin A1c (HbA1c), commonly referred to as glycated hemoglobin is widely recognized as a critical biomarker for both the diagnosis and long-term monitoring of diabetes. A threshold of 6.5% is recommended by international guidelines for diagnostic purposes (4). HbA1c remains the gold standard for assessing glycemic control, as it reflects average plasma glucose over the preceding 2 to 3 months (5).
High-performance liquid chromatography (HPLC)-based devices are regarded as the reference method for HbA1c measurement, owing to their high precision, reproducibility, and compatibility with long-term standardization programs (6). Although HPLC-based devices offer rapid and precise measurements, the requirement for costly instrumentation, technical expertise, and centralized laboratory infrastructure often renders them impractical in primary care environments or underserved regions with limited resources and low testing volumes.
To overcome these limitations, point-of-care (POC) HbA1c devices have been increasingly adopted. These devices enable rapid, on-site testing using small blood samples obtained via finger prick or venous sampling, and can be operated by non-laboratory personnel (7). A variety of POC HbA1c devices have been developed, employing distinct analytical principles. Commonly used systems include the DCA Vantage (latex-enhanced immunoassay), Afinion AS100 (boronate affinity chromatography), and Quo-Test (boronate affinity fluorometry) (8). Despite their convenience and increasing use in outpatient and community settings, these platforms differ substantially in detection chemistry, susceptibility to analytical interference (such as hemoglobin variants), and calibration stability. These factors may contribute to inconsistencies in measurement accuracy. Notably, deviations near key clinical thresholds, such as 6.5% for diagnosis or 7.0-8.0% for treatment decisions, may result in misclassification and inappropriate therapeutic interventions (9,10).
Given the increasing clinical reliance on POC testing, a comprehensive evaluation of their agreement with reference HPLC-based methods is essential. While several studies have assessed individual device performance, results remain inconsistent (11,12). For example, a prior meta-analysis reported substantial variability in bias across different POC platforms, with some devices showing deviations beyond clinically acceptable limits (10). Although international standardization efforts, led by the National Glycohemoglobin Standardization Program (NGSP) and International Federation of Clinical Chemistry and Laboratory Medicine (IFCC), have significantly improved the comparability of HbA1c results, the diversity of analytical principles employed by POC devices continues to pose challenges for ensuring consistent accuracy across platforms (13-15).
The aim of this systematic review and meta-analysis was to systematically assess the agreement between POC and HPLC-based laboratory methods for HbA1c measurement. Data on mean differences were pooled, subgroup analyses were conducted to explore heterogeneity, and device-specific factors that may affect measurement reliability were investigated. The findings are intended to inform clinicians, policymakers, and healthcare providers about the practical utility of POC HbA1c testing in routine diabetes care.
Discussion
The present systematic review and meta-analysis evaluated the agreement between POC HbA1c devices and laboratory HPLC-based methods, which are widely regarded as the reference standard for glycated hemoglobin measurement (6). Across 11 eligible studies comprising 3,285 paired measurements, it was found that most POC devices demonstrated acceptable agreement with HPLC, yielding a pooled mean difference of 0.01% (95% CI, -0.08 to 0.11%; P=0.779). This level of bias falls well within the clinically accepted margin of ±0.5%, suggesting that contemporary POC devices can provide clinically usable HbA1c measurements under appropriate conditions.
Notably, the 95% PI around the pooled estimate spanned nearly the full ±0.5% clinically acceptable margin and extended across the 6.5% diagnostic cut-off. This indicates that, although average agreement is favorable, individual devices or settings may yield values on opposite sides of the diagnostic threshold, particularly for patients near 6.5%. Therefore, even small systematic differences warrant careful interpretation at the individual-patient level.
However, the substantial heterogeneity across studies (I2 ~99.0%; Table SIV) indicates that the pooled estimate represents an average effect across diverse devices and settings rather than evidence of analytical interchangeability. Device-specific factors, testing environments, and patient characteristics therefore require careful consideration when interpreting individual results.
While some earlier studies documented devices with clinically unacceptable bias, our findings, excluding the i-Chroma, indicate that the majority of POC platforms meet the ±0.5% criterion for clinical agreement (10). This observation aligns with a previous meta-analysis which noted a non-significant trend toward less negative bias over time for the DCA device (coefficient 0.01% HbA1c per year; P=0.081), suggesting possible calibration improvements, although no significant temporal effect was observed for other devices (10,36,37). The findings of the present study reinforce this improvement and underscore the importance of device-specific evaluation, particularly for platforms such as lateral-flow chromatographic assay.
In addition, while a ±0.5% difference may be acceptable for population-level agreement, such variation could accumulate over time and influence longitudinal monitoring, particularly when clinical management relies on small changes in HbA1c.
Subgroup analyses provided additional insight but did not fully account for the substantial heterogeneity observed across studies. Stratification by device type, analytical principle, reference HPLC method, funding, exclusion of hemoglobin variants, specimen type, study setting, and other factors did not substantially reduce variability (Figs. 3, 4, and Fig. S1, Fig. S2, Fig. S3, Fig. S4, Fig. S5 and Fig. S6). This likely reflects the complex interplay of multiple factors inherent to in vitro diagnostic testing, including differences in reagent lots, calibration protocols, operator training, and environmental conditions. Previous reviews have emphasized that such variability remains a persistent challenge in standardizing HbA1c measurement across platforms and settings (10,35). Therefore, subgroup findings should be interpreted cautiously, and further large-scale standardized evaluations are needed to clarify sources of inconsistency.
Although the observed performance differences were not statistically attributable to analytical method, the underlying detection principles offer a useful framework for interpreting variability across devices. Boronate affinity chromatography, employed by devices such as Afinion and A1C EZ 2.0, targets cis-diol structures of glycated residues, regardless of glycation site (38). Although this method is generally robust and less affected by hemoglobin variants, its broader detection scope theoretically includes multiple glycated species beyond the IFCC-defined β-N-terminal glycation (38,39).
Notably, although manufacturer-level calibration can align these signals to the IFCC scale, the inherent detection characteristics of the method may introduce upward bias if non-target glycation is not sufficiently constrained. Therefore, potential method-based discrepancies in accuracy relate less to whether calibration occurs, and more to how tightly the underlying chemistry supports IFCC-conformant measurement.
By contrast, immunoassay-based methods depend on antibody specificity for HbA1c, making them more vulnerable to epitope changes, masking, or variant interference (40). Particularly, devices using lateral-flow formats add complexity due to open-system operation and manual handling, which may further compromise quantitative precision. While lateral-flow formats offer advantages in portability and ease of use, they are generally less precise due to their susceptibility to flow dynamics, operator variability, and lower analytical sensitivity (41). In addition, although enzymatic methods are widely used in centralized laboratories and rely on endoglycosidase digestion followed by quantification of released glycated amino acids, no studies of enzymatic POC platforms met our inclusion criteria (42-44). Consequently, the findings of the present study may not be generalizable to enzymatic systems, underscoring an important gap in the current evidence base.
From a practical standpoint, some studies evaluated POC devices using venous blood instead of capillary fingerstick samples, despite the devices being designed for the latter (30,33). While venous sampling improves methodological consistency and reduces pre-analytical variation, it may underestimate real-world variability. In decentralized settings, several additional factors may contribute to reduced accuracy, including operator training, sample collection technique, time from sampling to analysis, ambient environmental conditions (including temperature and humidity), and adherence to device-specific quality control protocols (13). Variability may also be amplified when testing is performed by non-laboratory personnel in community clinics, pharmacies, or home settings. Thus, analytical performance demonstrated under controlled conditions may not fully reflect achievable accuracy in routine practice.
An additional concern is analytical interference from hemoglobin variants or elevated fetal hemoglobin. Hemoglobin variants are genetically inherited structural alterations in the globin chains, commonly resulting from point mutations, deletions, or amino-acid substitutions. These variants include clinically prevalent types such as HbS (sickle cell), HbC, HbE, and HbD, which occur at relatively high frequencies in individuals of African, Mediterranean, and Southeast Asian descent (45). Depending on the nature and location of the mutation, these variants may interfere with HbA1c measurement through multiple mechanisms: Altering the glycation site, affecting the charge or conformation of the protein, or modifying red blood cell lifespan (46). Beyond structural variants, conditions associated with altered erythrocyte turnover, such as anemia or chronic kidney disease, may also bias HbA1c values independent of analytical method.
Therefore, in individuals with suspected or known hemoglobinopathies, HbA1c should be interpreted with caution, and alternative markers such as glycated albumin or fructosamine may be more appropriate. Clinically, the presence of hemoglobin variants significantly limits the reliability of HbA1c measurements. As a result, the standard diagnostic cutoff of 6.5% may not be valid in these populations. Guidelines from the ADA and WHO recommend alternative diagnostic approaches, such as fasting glucose, OGTT, or short-term glycation markers (such as fructosamine and glycated albumin), when hemoglobinopathies are suspected or confirmed (47,48). Notably, ion-exchange method and capillary electrophoresis can provide variant information on the result graph, which provides an essential clinical application (49).
The present study has several strengths, including a comprehensive search strategy, strict inclusion criteria requiring HPLC as the reference standard, and the use of standardized agreement metrics. Subgroup analyses were conducted, and pooled estimates remained consistent across analytic approaches, supporting the robustness of our findings. However, certain limitations should be noted. The number of included studies was relatively small, and several devices were represented by only one or two datasets, limiting statistical power and generalizability. Numerous studies lacked detailed reporting on calibration protocols, quality control measures, and management of analytical interference. Additionally, our analysis focused primarily on analytical agreement rather than diagnostic accuracy, clinical outcomes, or cost-effectiveness, which are critical for real-world adoption.
Future research should prioritize large-scale implementation studies that assess device performance in decentralized settings, account for operator variability, and evaluate resilience under environmental stressors such as temperature and humidity. Head-to-head comparative studies across multiple platforms and integration of advanced calibration technologies, including AI-assisted algorithms and real-time connectivity, may enhance precision and usability. Transparent reporting of calibration strategies, interference susceptibility, and practical deployment metrics will be essential to inform clinical decision-making and regulatory guidance.
In conclusion, this systematic review and meta-analysis demonstrates that most POC HbA1c devices show acceptable analytical agreement with reference HPLC methods. However, substantial heterogeneity persists, emphasizing the importance of local validation before widespread adoption. Future research should prioritize standardized protocols and real-world implementation studies to enhance reliability and comparability.